遗传算法结合响应面法优化番茄红素纳米结构脂质载体的制备

目的 提高脂溶性番茄红素的生物利用率和稳定性。方法 采用熔融-高速剪切法制备番茄红素纳米结构脂质载体。以包封率、平均粒径为主要评价指标，进行单因素实验，并在单因素基础上通过遗传算法结合Box-Behnken响应面法对制备工艺进行优化。结果 遗传算法和Box-Behnken响应面法优化得到的理论包封率分别为86.208 2%、86.169 5%。通过验证实验得到实际包封率为(86.267±0.44)%，平均粒径为(121.8±5.20)nm。结论 结果表明遗传算法结合Box-Behnken响应面法优化番茄红素纳米结构脂质载体模型可靠。

Optimization of Preparation of Lycopene Nanostructured Lipid Carrier by Genetic Algorithm Combined with Response Surface Method

In order to improve the bioavailability and stability of fat soluble lycopene, lycopene nanostructured lipid carriers were prepared by melting high-speed shear method. Taking the entrapment efficiency and average particle size as the main evaluation indexes, the single factor test was carried out, and the preparation process was optimized by genetic algorithm combined with Box-Behnken response surface method. The theoretical entrapment efficiencies optimized by genetic algorithm and Box-Behnken response surface method are 86.208 2% and 86.169 5%. By validation test, the actual entrapment efficiency and average particle size were (86.267±0.44)% and (121.8±5.20)nm. The results show that the optimization of lycopene nanostructured lipid carrier model by genetic algorithm combined with Box-Behnken response surface method is reliable.